时变O-U模型在气温预测及气温期货定价中的适应性研究——基于北京市1951-2012年的日平均气温数据

doi:10.16381/j.cnki.issn1003-207x.2015.02.006

中国管理科学 ›› 2015, Vol. 23 ›› Issue (2): 44-49.doi: 10.16381/j.cnki.issn1003-207x.2015.02.006

时变O-U模型在气温预测及气温期货定价中的适应性研究——基于北京市1951-2012年的日平均气温数据

王明亮¹, 何建敏¹, 陈百硕¹, 曹杰²

1. 东南大学经济管理学院, 江苏南京 211189;
2. 南京信息工程大学经济管理学院, 江苏南京 210044

收稿日期:2012-10-24 修回日期:2013-09-17 出版日期:2015-02-20 发布日期:2015-02-28
作者简介:王明亮(1987-),男(汉族),山东日照人,东南大学经济管理学院研究生,研究方向:金融分析与金融工程.
基金资助:
公益性行业(气象)科研专项(GYHY201106019);国家自然科学基金资助项目(71071034,71201023,71371051)

The Adaptive Research of the Time-varying O-U Model in the Pricing of Weather Derivatives-A Case Study of Beijing

WANG Ming-liang¹, HE Jian-min¹, CHEN Bai-shuo¹, CAO Jie²

1. School of Economics and Management, Southeast University, Nanjing 211189, China;
2. School of Economics and Management, Nanjing University of Information Science & Technology, Nanjing 210044, China

Received:2012-10-24 Revised:2013-09-17 Online:2015-02-20 Published:2015-02-28

摘要/Abstract

摘要： 天气衍生品作为一种规避天气风险的金融衍生品,如何对其准确定价一直以来是学术界争论的焦点。文章以Alaton^[5]提出的基于月波动率的O-U模型为基础,将原模型中的常量均值回复速率考虑为随时间变化的变量,并通过ARMA(p, q)模型分析该时间序列的变化规律,进而建立时变O-U模型。基于北京市自1951年以来的日平均气温数据,分别模拟了2010-2012共计三年的日平均气温,并与其真实值对比发现:改进后的模型残差平方和更小,而偏差比例、方差比例和协方差比例也显示改进后的模型对温度预测效果更好。最后,基于北京市的数据通过蒙特卡洛仿真计算了CDDs和HDDs,并进行了相关的期货合约定价,进一步验证了改进后模型的适应性。

关键词: 天气衍生品, O-U模型, 均值回复速率, 蒙特卡洛仿真

Abstract: How to accurately price the weather derivatives,which as a sort of weather risk-hedging financial derivatives, has always been the focus of academic debate. Based on the O-U model of monthly volatility presented by Alaton^[5], the speed of mean reversion is considered in this paper,which is a constant in the original model as a time-dependent variable. Then the time sequence of the speed of mean reversion is analyied by ARMA(p, q) model and establish the time-varying O-U model. Based on Beijing's daily average temperature data from 1951, three years of daily average temperature from 2010 to 2012 are simulated respectirely, and compared with its true value. After the comparison,it is found that: the residual sum of squares of the improved model are smaller, meanwhile the bias proportion, the variance proportion and the covariance proportion also show the improved model obtains a better temperature prediction. Finally, the CDDs are calculated and HDDs are calculated according to Beijing's daily average temperature data by Monte Carlo simulation, and then price the related futures contract to further validate the adaptability of improved model.

Key words: weather derivatives, O-U model, speed of mean reversion, Monte Carlo simulation

中图分类号:

F830.9

王明亮, 何建敏, 陈百硕, 曹杰. 时变O-U模型在气温预测及气温期货定价中的适应性研究——基于北京市1951-2012年的日平均气温数据[J]. 中国管理科学, 2015, 23(2): 44-49.

WANG Ming-liang, HE Jian-min, CHEN Bai-shuo, CAO Jie. The Adaptive Research of the Time-varying O-U Model in the Pricing of Weather Derivatives-A Case Study of Beijing[J]. Chinese Journal of Management Science, 2015, 23(2): 44-49.

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时变O-U模型在气温预测及气温期货定价中的适应性研究——基于北京市1951-2012年的日平均气温数据

The Adaptive Research of the Time-varying O-U Model in the Pricing of Weather Derivatives-A Case Study of Beijing

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